A Study on Genotype-by-Environment Interaction Analysis for Agronomic Traits of Maize Genotypes Across Huang-Huai-Hai Region in China

Abstract

Facing the trend of increasing population, how to increase maize grain yield is a very important issue to ensure food security. In this study, 28 nationally approved maize hybrids were evaluated across 24 different climatic conditions for two consecutive years (2018)(2019). The purpose of this study was to select high-yield with stable genotypes and identify important agronomic traits for maize breeding program improvement. The results of this study showed that the genotype  environment interaction effects of the 12 evaluated agronomic traits was highly significant (P < 0.001). We introduced a novel multi-trait genotype-ideotype distance index (MGIDI) to select genotypes based on multiple agronomic traits. The selection process exhibited by this method is unique and easy to understand, so the MGIDI index will have more and more important applications in future multi-environment trials (METs) research. The genotypes selected by the MGIDI index were G22, G10, G12 and G1 as the high yielding and stable genotypes. The parents of these selected genotypes have the ability to play a greater role as the basic germplasm in the breeding process. A new form of genotype (G) main effects and genotype (G) -by-environment (E) interaction (GGE) technician, genotype à yield à trait (GYT) biplot, based on multiple traits for genotypes selection was also applied in this study. The GYT biplot ranked genotypes by combining grain yield with other evaluated agronomic traits, and displayed the distribution of their traits, namely strengths and weaknesses.

Detection of Superior Rice Genotypes and Yield Stability under Different Nitrogen Levels Using AMMI Model and Stability Statistics

“…GY is a quantitative trait determined by the additive main effect of environment (E) and genotype (G) in addition to the nonadditive effect of the G X E interaction (GEI) [ 9 ]. Breeders focus on the GEI effect to identify the yield stability of genotypes across different conditions and environments, which cannot be revealed by the separate effects of genotype or environment [ 10 , 11 , 12 , 13 , 14 ]. The GY heritability is exposed to variability across different environments [ 15 , 16 ], which hinders the accuracy of superior varietal selection processes [ 17 ].…”

Multi-trait selection for mean performance and stability of maize hybrids in mega-environments delineated using envirotyping techniques

“…A total of 9 yield-related agronomic traits were recorded in this study. Agronomic traits viz., grain yield (GY, t ha -1 ) was manually harvested from the middle three rows, adjusting the moisture to 14% and converting the unit to tons per hectare; grain moisture content (GMC, %), measured from each plant at each plot; plant height (PH, cm), measured from the base of the root to the top of the tassel; ear height (EH, cm), measured from the base of the root to the stalk of the ear; ear length (EL, cm), measured from the line up 10 ears, and dividing the data obtained by 10; ear row (ER), counting the total number of rows in each ear; bare tip length (BTL, cm), measured from the top part with no grains (if any) to the part with grains; grain weight per ear (GWE, g) and 100-seed weight (HSW, g) ( Yue et al., 2022a ).…”

“…The Huanghuaihai (HHH) plain ( Figure 1 ) is the largest concentrated summer maize planting area in China, accounting for 31.86% and 30.68% of the country’s total area and yield, respectively ( Zhai et al., 2022 ). The meteorological conditions in the HHH plain are complex, often encountering high temperatures, heat damage, cloudy rain and lack of sunshine, and the invasion of various diseases, which make maize yields vary greatly from year to year ( Wang et al., 2020 ; Shi et al., 2021 ; Yue et al., 2022b ). Unencouraging climate change projections suggest that the temperature increase might be a key factor affecting the drought risk in HHH ( Yue et al., 2022c ).…”

Dissection of genotype-by-environment interaction and simultaneous selection for grain yield and stability in faba bean (Vicia fabaL.)

“…Consequently, Olivoto et al (2019) integrated the graphical tools of the AMMI model into the BLUP technique and developed a new stability statistic, WAASB (weighted average of absolute scores). The WAASB has been used to identify high-yielding stable genotypes in many crops (Koundinya et al, 2021; Nataraj et al, 2021; Pour-Aboughadareh et al, 2022b; Yue et al, 2022), but not in faba bean.…”